The physical properties of polymers depend on a range of both structural and chemical parameters, and in particular, on molecular topology. Apparently simple changes such as joining chains at a point to form stars or simply joining the two ends to form a ring can profoundly alter molecular conformation and dynamics, and hence properties. Cyclic polymers, as they do not have free ends, represent the simplest model system where reptation is completely suppressed. As a consequence, there exists a considerable literature and several reviews focused on high molecular weight cyclics where long range dynamics described by the reptation model comes into play. However, this is only one area of interest. Consideration of the conformation and dynamics of rings and chains, and of their mixtures, over molecular weights ranging from tens of repeat units up to and beyond the onset of entanglements and in both solution and melts has provided a rich literature for theory and simulation. Experimental work, particularly neutron scattering, has been limited by the difficulty of synthesizing well-characterized ring samples, and deuterated analogues. Here in the context of the broader literature we review investigations of local conformation and dynamics of linear and cyclic polymers, concentrating on poly(dimethyl siloxane) (PDMS) and covering a wide range of generally less high molar masses. Experimental data from small angle neutron scattering (SANS) and quasi-elastic neutron scattering (QENS), including Neutron Spin Echo (NSE), are compared to theory and computational predictions.Taking China's carbon emissions and trading pilot (CCETP) as a quasi-natural experiment, this paper examines the impact of CCETP on publicly listed private firms' innovation input and the moderating effect of the firms' political connection based on the difference-in-differences model. The results show that CCETP has a significantly positive effect on the innovation input of Chinese publicly listed private firms. Moreover, the political connection of executives exhibits a positive moderating effect on CCETP's impact on innovation input. Meanwhile, the effect is more significant in regions with high environmental protection investment and large publicly listed private firms. The conclusions could provide some policy enlightenment for China's carbon market, as well as a rational adjustment of the relationship between political connection and innovation input of publicly listed private firms in the future.This study examined physiological and race pace characteristics of medium- (finish time 240 min) recreational runners who participated in a challenging marathon route with rolling hills, the Athens Authentic Marathon. Fifteen athletes (age 42 ± 7 years) performed an incremental test, three to nine days before the 2018 Athens Marathon, to determine maximal oxygen uptake (VO2 max), maximal aerobic velocity (MAV), energy cost of running (ECr) and lactate threshold velocity (vLTh), and were analyzed for their pacing during the race. Moderate- (n = 8) compared with low-level (n = 7) runners had higher (p less then 0.05) VO2 max (55.6 ± 3.6 vs. 48.9 ± 4.8 mL?kg-1?min-1), MAV (16.5 ± 0.7 vs. 14.4 ± 1.2 km?h-1) and vLTh (11.6 ± 0.8 vs. 9.2 ± 0.7 km?h-1) and lower ECr at 10 km/h (1.137 ± 0.096 vs. 1.232 ± 0.068 kcal?kg-1?km-1). Medium-level runners ran the marathon at a higher percentage of vLTh (105.1 ± 4.7 vs. 93.8 ± 6.2%) and VO2 max (79.7 ± 7.7 vs. 68.8 ± 5.7%). https://www.selleckchem.com/products/cetirizine.html Low-level runners ran at a lower percentage (p less then 0.05) of their vLTh in the 21.1-30 km (total ascent/decent 122 m/5 m) and the 30-42.195 km (total ascent/decent 32 m/155 m) splits. Moderate-level runners are less affected in their pacing than low-level runners during a marathon route with rolling hills. This could be due to superior physiological characteristics such as VO2 max, ECr, vLTh and fractional utilization of VO2 max. A marathon race pace strategy should be selected individually according to each athlete's level.Oxide dispersion strengthened (ODS) alloys with Al and Zr addition have excellent radiation tolerance, high-temperature strength, and corrosion resistance. The 15Cr-Al-Zr-ODS alloys are processed by mechanical alloying (MA), hot isostatic pressing (HIP), subsequent hot rolling to large strains of 70%, and further annealing. The effect of hot rolling on the microstructure, and the properties of nanostructured 15Cr ODS alloys with Al and Zr addition, were investigated. The microstructure after hot rolling and annealing showed obvious anisotropy. The cubic texture (φ1 = 0°, Φ = 0°, φ2 = 0°) 0 0 1 were observed. The similar size distribution of precipitates was obtained for the comparison of the hot rolling samples with the hot isostatic pressed samples, which can be attributed to excellent thermal stability. After hot rolling, the alloy showed higher yield strength but did not lose too much plasticity.Emotion recognition based on physiological data classification has been a topic of increasingly growing interest for more than a decade. However, there is a lack of systematic analysis in literature regarding the selection of classifiers to use, sensor modalities, features and range of expected accuracy, just to name a few limitations. In this work, we evaluate emotion in terms of low/high arousal and valence classification through Supervised Learning (SL), Decision Fusion (DF) and Feature Fusion (FF) techniques using multimodal physiological data, namely, Electrocardiography (ECG), Electrodermal Activity (EDA), Respiration (RESP), or Blood Volume Pulse (BVP). The main contribution of our work is a systematic study across five public datasets commonly used in the Emotion Recognition (ER) state-of-the-art, namely (1) Classification performance analysis of ER benchmarking datasets in the arousal/valence space; (2) Summarising the ranges of the classification accuracy reported across the existing literature; (3) Characterising the results for diverse classifiers, sensor modalities and feature set combinations for ER using accuracy and F1-score; (4) Exploration of an extended feature set for each modality; (5) Systematic analysis of multimodal classification in DF and FF approaches. The experimental results showed that FF is the most competitive technique in terms of classification accuracy and computational complexity. We obtain superior or comparable results to those reported in the state-of-the-art for the selected datasets.